/// <summary>
/// Multiply matrix times scalar
/// </summary>
/// <param name="a"></param>
/// <param name="b"></param>
/// <returns>A new matrix with entry [i,j] equal to a*b[i,j]</returns>
public static PositiveDefiniteMatrix operator *(double a, PositiveDefiniteMatrix b)
{
PositiveDefiniteMatrix result = (PositiveDefiniteMatrix)b.Clone();
result.Scale(a);
return(result);
}
/// <summary>
/// Multiply matrix times scalar
/// </summary>
/// <param name="a"></param>
/// <param name="b"></param>
/// <returns>A new matrix with entry [i,j] equal to a[i,j]*b</returns>
public static PositiveDefiniteMatrix operator *(PositiveDefiniteMatrix a, double b)
{
PositiveDefiniteMatrix result = (PositiveDefiniteMatrix)a.Clone();
result.Scale(b);
return(result);
}
/// <summary>
/// Adds a weighted observation.
/// </summary>
/// <param name="x"></param>
/// <param name="weight"></param>
public void Add(Vector x, double weight)
{
// new_mean = mean + w/(count + w)*(x - mean)
// new_cov = count/(count + w)*(cov + w/(count+w)*(x-mean)*(x-mean)')
count += weight;
if (count == 0)
{
return;
}
diff.SetToDifference(x, mean);
double s = weight / count;
mean.SetToSum(1.0, mean, s, diff);
//outer.SetToOuter(diff,diff2);
// this is more numerically stable:
//outer.SetToOuter(diff, diff).Scale(s);
cov.SetToSumWithOuter(cov, s, diff, diff);
cov.Scale(1 - s);
}
